Combating climate change by increasing urban carbon storage is one of the critical issues which urban policymakers must address. Understanding the characteristics and driving factors of carbon storage changes during urbanization can assist urban managers in formulating responsive land use policies. This study employs the INVEST model to evaluate carbon storage in Shanghai from 2000 to 2020, analyzing land use changes and their carbon impacts. It analyzes the transformation of land use in Shanghai during the same period and its impact on carbon storage. Using a 1 km grid for sampling, this study examines the spatiotemporal distribution patterns of carbon storage in Shanghai. Furthermore, it employs linear regression to discuss the social and economic drivers influencing carbon storage in the city. Carbon storage in Shanghai, predominantly from cultivated land and artificial surfaces, increased from 16.78 Mt in 2000 to 18.40 Mt in 2020, with an annual rise of 0.81 Mt. The spatial distribution of carbon storage exhibited a stable southeast-northwest pattern, with variations in dispersion between the north-south and east-west directions. The distribution of carbon storage shifted from a bimodal to a unimodal pattern, indicating an overall increase. There was a significant positive correlation between carbon storage and both the per capita green space area and the industrial output value, which can be attributed to Shanghai’s policies on green industrial development. This research aids in formulating land use policies to enhance urban carbon storage.

Particulate matter (PM) in urban riparian green spaces are undesirable for human participation in outdoor activities, especially PM_2.5 and PM₁₀. The PM deposition, dispersion and modification are influenced by various factors including vegetation, water bodies and meteorological conditions. This study aimed to investigate the impact of vegetation structures and the river’s presence on PM in riparian zones. The spatial-temporal variations of PM_2.5 and PM₁₀ concentrations in three riparian vegetation communities with different structures (open grassland (G), arbor-grass (AG) and arbor-shrub-grass (ASG) woodlands) were monitored under relatively stable environment. The removal percentages (RP) and ratios of PM_2.5 and PM₁₀ were calculated and compared to identify the removal effect of vegetation structures and the river’s presence. It is found that: (1) when the wind was static (hourly wind speed < 0.2 m/s), the RP was ranked as follows: G > AG > ASG. When the wind was mild (0.2 m/s < hourly wind speed < 2 m/s), the RP was ranked as follows: G > ASG > AG. Generally, the G had the best removal effect during the monitoring period; (2) the lowest RP occurred in the middle of the G (–3.4% for PM_2.5, 1.8% for PM₁₀) while the highest RP were found in middle of the AG and ASG, respectively (AG: 2.1% for PM_2.5, 6.7% for PM₁₀; ASG: 2.4% for PM_2.5, 6.3% for PM₁₀). Vegetation cover changed the way of natural deposition and dispersion; (3) compared with static periods, PM removal percentages were significantly reduced under mild wind conditions, and they were positively correlated with wind speed during the mild-wind period. Thus, a piecewise function was inferred between wind speed and PM removal percentage; (4) for all three communities, the 1 m-to-river PM_2.5/PM₁₀ ratio was significantly lower than that at 6 m and 11 m, even lower than that in the ambient atmosphere. The river likely promoted the hygroscopic growth of PM_2.5 and the generation of larger-sized particles by coagulation effect. Based on these findings, open grassland space is preferred alongside rivers and space for outdoor activities is suggested under canopies in the middle of woodlands.

The interactions between CO₂ flux, an important component of ecosystem carbon flux, and climate change vary significantly among different ecosystems. In this research, the inter-annual variation characteristics of ecosystem respiration (RE), gross ecosystem exchange (GEE), and net ecosystem exchange (NEE) were explored in the temperate grassland (TG) of Xilinhot (2004–2010), the subtropical artificial coniferous forest (SACF) of Qianyanzhou (2003–2010), and the tropical rain forest (TRF) of Xishuangbanna (2003–2010). The main factors of climate change affecting ecosystem CO₂ flux were identified by redundancy analysis, and exponential models and temperature indicators were constructed to consider the relationship between climate change and CO₂ flux. Every year from 2003 to 2010, RE and GEE first increased and then decreased, and NEE showed no significant change pattern. TG was a carbon source, whereas SACF and TRF were carbon sinks. The influence of air temperature on RE and GEE was greater than that of soil temperature, but the influence of soil moisture on RE and GEE was greater than that of air moisture. Compared with moisture and photosynthetically active radiation, temperature had the greatest impact on CO₂ flux and the exponential model had the best fitting effect. In TG and SACF, the average temperature was the most influential factor, and in TRF, the accumulated temperature was the most influential factor. These results provide theoretical support for mitigating and managing climate change and provide references for achieving carbon neutrality.

Urban flooding, intensified by climate change, poses significant threats to sustainable development, necessitating accurate precipitation projections for effective risk management. This study utilized Bayesian Model Averaging (BMA) to optimize CMIP6 multi-model ensemble precipitation projections for Shanghai, integrating Delta statistical downscaling with observational data to enhance spatial accuracy and reduce uncertainty. After downscaling, RMSE values of daily precipitation for individual models range from 10.158 to 12.512, with correlation coefficients between −0.009 and 0.0047. The BMA exhibits an RMSE of 8.105 and a correlation coefficient of 0.056, demonstrating better accuracy compared to individual models. The BMA-weighted projections, coupled with Soil Conservation Service Curve Number (SCS-CN) hydrological model and drainage capacity constraints, reveal spatiotemporal flood risk patterns under Shared Socioeconomic Pathway (SSP) 245 and SSP585 scenarios. Key findings indicate that while SSP245 shows stable extreme precipitation intensity, SSP585 drives substantial increases—particularly for 50-year and 100-year return periods, with late 21st century maximums rising by 24.9% and 32.6%, respectively, compared to mid-century. Spatially, flood risk concentrates in peripheral districts due to higher precipitation exposure and average drainage capacity, contrasting with the lower-risk central urban core. This study establishes a watershed-based risk assessment framework linking climate projections directly to urban drainage planning, proposing differentiated strategies: green infrastructure for runoff reduction in high-risk areas, drainage system integration for vulnerable suburbs, and ecological restoration for coastal zones. This integrated methodology provides a replicable approach for climate-resilient urban flood management, demonstrating that effective adaptation requires scenario-specific spatial targeting.

This paper selects the theory of "carbon source, carbon sink and carbon neutralization" witch has high applicability in the "dual-carbon" target theory, to clarify the construction of low-carbon community open space under the "dual-carbon" target. Discuss the realization of low-carbon community open space under this theory, and build the target layer and secondary indicator layer of low-carbon open space construction management indicators based on this theory. Fifty representative indicators related to the open space in low-carbon communities are selected from the eight widely used evaluation index systems in the world. According to the implementation path of the "double carbon" goal of the open space in low-carbon communities, these indicators are divided into six categories: "energy utilization", "resource utilization", "transportation", "carbon pool", "carbon absorption" and "low-carbon community management and culture”. Take the six categories as framework, combined with current condition and research status in China, the relevant indicators of "carbon absorption" are supplemented, and a low-carbon community open space management index system including three first-class indicators, six secondary indicators and twenty-eight tertiary indicators is constructed.